WO2020051046A1 - Interférométrie à longueurs d'onde multiples pour la classification de défauts - Google Patents

Interférométrie à longueurs d'onde multiples pour la classification de défauts Download PDF

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Publication number
WO2020051046A1
WO2020051046A1 PCT/US2019/048680 US2019048680W WO2020051046A1 WO 2020051046 A1 WO2020051046 A1 WO 2020051046A1 US 2019048680 W US2019048680 W US 2019048680W WO 2020051046 A1 WO2020051046 A1 WO 2020051046A1
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Prior art keywords
defect
illumination
sample
inspection system
sheared
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PCT/US2019/048680
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English (en)
Inventor
Andrew Zeng
Helen Liu
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Kla Corporation
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Application filed by Kla Corporation filed Critical Kla Corporation
Priority to JP2021535488A priority Critical patent/JP7219818B2/ja
Priority to CN201980057650.0A priority patent/CN112654859B/zh
Priority to KR1020217009726A priority patent/KR102545425B1/ko
Priority to CN202210550590.XA priority patent/CN114858809A/zh
Publication of WO2020051046A1 publication Critical patent/WO2020051046A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00—Measuring instruments characterised by the use of optical techniques
    • G01B9/02—Interferometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B9/00—Measuring instruments characterised by the use of optical techniques
    • G01B9/02—Interferometers
    • G01B9/02015—Interferometers characterised by the beam path configuration
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8806—Specially adapted optical and illumination features
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/9501—Semiconductor wafers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
    • G01N21/956—Inspecting patterns on the surface of objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8854—Grading and classifying of flaws
    • G01N2021/8858—Flaw counting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10141—Special mode during image acquisition
    • G06T2207/10152—Varying illumination

Definitions

  • the present disclosure relates generally to defect classification in semiconductor fabrication and, more particularly, to multi-wavelength interferometry for defect classification.
  • Defect detection is a critical step in a semiconductor fabrication process and may be performed at various stages of fabrication to control yield. Further, it may be desirable to identify the composition of an identified defect to facilitate determination of the root cause of the defect. For example, identifying whether an identified particle on a sample is metal or non-metal (e.g., a dielectric) may provide insight into the source of the contamination.
  • metal or non-metal e.g., a dielectric
  • composition analysis may typically be performed using a separate tool such as an energy-dispersive X-ray (EDX) tool, which may suffer from relatively long measurement times that negatively impact throughput. Additionally, transferring samples between tools may potentially expose samples to further contaminants as well as further decreasing the throughput. There is therefore a need to develop systems and methods to cure the above deficiencies.
  • EDX energy-dispersive X-ray
  • the system includes a controller communicatively coupled to a differential interference contrast imaging tool configured to generate one or more images of a sample based on illumination with two sheared illumination beams, where an illumination spectrum of the two sheared illumination beams and an induced phase difference between the two sheared illumination beams are selectable for any particular image of the sample.
  • the controller receives a first set of images of a defect on the sample with a first selected illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams.
  • the controller determines a first defect-induced phase shift based on the first selected illumination spectrum. In another illustrative embodiment, the controller receives a second set of images of a defect on the sample with a second selected illumination spectrum different than the first illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams. In another illustrative embodiment, the controller determines a second defect-induced phase shift based on the second selected illumination spectrum in another illustrative embodiment, the controller classifies the defect as a metal or a non-metal based on a comparison of the first phase shift to the second phase shift.
  • the system includes a differential interference contrast imaging tool to generate one or more images of the sample based on illumination with two sheared illumination beams, where an illumination spectrum of the two sheared illumination beams and a phase difference between the two sheared illumination beams are selectable for any particular image of the sample.
  • the system includes a controller communicatively coupled to the imaging tool in another illustrative embodiment, the controller receives a first set of images of a defect on the sample with a first selected illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams.
  • the controller determines a first phase shift associated with the defect based on the first selected illumination spectrum. In another illustrative embodiment, the controller receives a second set of images of a defect on the sample with a second selected illumination spectrum different than the first illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams. In another illustrative embodiment, the controller determines a second phase shift associated with the defect based on the second selected illumination spectrum. In another illustrative embodiment, the controller classifies the defect as a metal or a non-metal based on a comparison of the first phase shift to the second phase shift.
  • the method includes receiving a first set of images of a defect on a sample with a first selected illumination spectrum and two or more selected induced phase differences between two sheared illumination beams from a differential interference contrast imaging tool.
  • the method includes determining a first defect-induced phase shift based on the first selected illumination spectrum.
  • the method includes receiving a second set of images of a defect on the sample with a second selected illumination spectrum different than the first illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams from the differential interference contrast imaging tool in another illustrative embodiment, the method includes determining a second defect-induced phase shift based on the second selected illumination spectrum. In another illustrative embodiment, the method includes classifying the defect as a metal or a non-metal based on a comparison of the first defect-induced phase shift to the second defect-induced phase shift,
  • FIG. 1 is a conceptual view of a DIG inspection system in accordance with one or more embodiments of the present disclosure.
  • FIG. 2 is a simulated plot of the RPC of Tungsten (W) and Copper (Cu) on a silicon substrate as a function of thickness at a wavelength of 365 nm, in accordance with one or more embodiments of the present disclosure.
  • FIG. 3 is a simulated plot of the RPC of S1O2 on a silicon substrate as a function of thickness at a wavelength of thickness at a wavelength of 365 nm, in accordance with one or more embodiments of the present disclosure.
  • FIG. 4 is a plot of copper (Cu) on a silicon substrate as a function of thickness, in accordance with one or more embodiments of the present disclosure.
  • FIG. 5 is a plot of copper SiC on a silicon substrate as a function of thickness, in accordance with one or more embodiments of the present disclosure.
  • FIG. 6 includes simulated plots of the intensity of a defect generated using multiple sequential scans with four different selected system-induced phase shifts, in accordance with one or more embodiments of the present disclosure.
  • FIG. 7 includes a plot of a defect profile and a plot of simulated and reconstructed defect- induced phase-shifts based on the plots in FIG. 6, in accordance with one or more embodiments of the present disclosure.
  • FIG. 8 includes three measured images of a sample without a defect, in accordance with one or more embodiments of the present disclosure.
  • FIG. 9 is a plot of a reconstructed phase-shift of the sample imaged in FIG. 8, in accordance with one or more embodiments of the present disclosure.
  • FIG. 10 is a flow diagram illustrating steps performed in a method for classifying defects, in accordance with one or more embodiments of the present disclosure.
  • Embodiments of the present disclosure are directed to systems and methods for multi-wavelength interference-based microscopy to provide both defect identification (e.g., detecting the presence of defects) and classification of the composition of an identified defect based on a reflected phase change (RPC) of the defect.
  • defect identification e.g., detecting the presence of defects
  • RPC reflected phase change
  • RPC reflection phase change
  • a defect may be both identified (e.g., detected) and classified using multi-wavelength differential interference contrast (DIC) microscopy.
  • a DIC inspection system may generate an image of a sample, or a portion thereof, by shearing an illumination beam into two sheared beams, illuminating the sample with the sheared beams, and recombining the sheared beams to form an image captured by a detector. Contrast in the corresponding image (e.g., variations in intensity of light and thus detected signal strength) is related to interference the combined sheared beams at the detector based on an optical phase of the combined light on the detector.
  • This optical phase may be influenced by multiple factors including, but not limited to, an optical path difference (QPD) between optical paths of the two sheared beams as they propagate through the system and reflect off of the sample, a difference between the RPC introduced to the two sheared beams upon reflection.
  • QPD optical path difference
  • the presence of a defect on the sample may induce a phase shift associated with both an OPD based on the defect height as well as an RPC difference between the defect and the surrounding material.
  • a D1C inspection system may further introduce a phase shift based on the particular configuration of components in the optical paths of the sheared beams.
  • the optical paths of the sheared beams may differ based on the position and/or orientation of the shearing prism.
  • Additional embodiments of the present disclosure are directed to performing a phase retrieval analysis to extract or otherwise isolate the contribution of a defect to a DIC signal.
  • a DIG inspection system may utilize a phase shifting technique to isolate the defect-induced phase shift based on multiple images of a sample with different induced phase offsets between the sheared illumination beams.
  • Additional embodiments of the present disclosure are directed to classifying a defect based on comparing a defect-induced phase shift associated with two or more wavelengths.
  • a DIC inspection system may image a sample, or a portion thereof, with two or more wavelengths and classify identified defects based on a comparison of defect-induced phase shifts for each wavelength. Further, the DIC inspection system may perform a phase retrieval analysis based on multiple images at each wavelength to extract the defect-induced OPD for each wavelength.
  • the RPC of metals may be substantially constant as a function of wavelength, whereas the RPC of many non-metals such as, but not limited to, dielectrics may vary as a function of wavelength.
  • comparing the defect-induced phase shift (or a difference in RPC between a defect and surrounding material if determined directly) generated with different wavelengths may provide insight into the composition of a defect.
  • an identified defect may be classified by determining a ratio of defect-induced phase shifts generated with two different wavelengths.
  • a defect may be classified as metallic when the ratio is within a selected tolerance of 1 , and may be classified as a nonmetal (e.g., dielectric) otherwise.
  • the RPC is extracted or otherwise isolated from the defect-induced OPD.
  • the contribution of the defect height which does not vary with imaging wavelength, may be removed.
  • a defect may be classified based on a comparison of the RPC at two or more wavelengths.
  • the RPC of particular materials e.g., particular metals or dielectric materials
  • the composition of the defect may be identified based on a comparison of measured values of the RPC to these known values.
  • FIGS. 1 through 9 systems and methods for defect identification and classification based on multi-wavelength differential interference contrast (DIC) inspection are described in accordance with one or more embodiments of the present disclosure.
  • DIC differential interference contrast
  • FIG. 1 is a conceptual view of a DIC inspection system 100 in accordance with one or more embodiments of the present disclosure.
  • the DIC inspection system 100 includes an illumination source 102 to generate an illumination beam 104, a shearing prism 106 to split the illumination beam 104 into two sheared beams 108 separated along a shearing direction 1 10, an objective lens 112 to direct the two sheared beams 108 to a sample 1 14 at spatially-separated locations, and a detector 116 to capture an image of the sample 114 based on the interference between the two sheared beams 108.
  • the sample 1 14 is illustrated as a substrate 1 18 and a defect 120.
  • the sample 1 14 may be mounted on a translation stage 122 to control the position of the sample 1 14 within a field of view of the DIC inspection system 100.
  • the translation stage 122 may include, but is not limited to, any combination of linear, rotation, or tip/tilt actuators.
  • the objective lens 112 further collects portions of the sheared beams 108 reflected from the sample 1 14 (e.g., reflected light 124) such that the reflected light 124 associated with the two sheared beams 108 is recombined by the shearing prism 106 along a common optical path.
  • the DIG inspection system 100 may include a beamsplitter 126 to separate the illumination beam 104 from the combined reflected light 124 along the common optical path towards the detector 1 16.
  • the shearing prism 106 may be any type of optical element known in the art suitable for shearing the illumination beam 104 into two sheared beams 108.
  • the shearing prism 106 may include a polarizing prism that separates the illumination beam 04 into sheared beams 108 based on polarization.
  • the sheared beams 108 may include a Nomarski prism, a Wollaston prism, a Rochon prism, or the like, where the two sheared beams 108 correspond to ordinary and extraordinary rays.
  • the DIC inspection system 100 includes a phase- adjustment sub-system 128 configured to introduce, adjust, or otherwise control a relative optical path difference (OPD) between the optical paths of the two sheared beams 108 through the system, including reflection by the sample 114.
  • the phase-adjustment sub-system 128 may include an actuator (e.g., a translation stage, or the like) coupled to a mount securing the shearing prism 106.
  • the phase-adjustment sub-system 128 may control the OPD between the sheared beams 108 by adjusting a position of the shearing prism 106.
  • the phase-adjustment sub-system 128 may include a de Senarmont compensator.
  • the DIC inspection system 100 includes one or more polarization-controlling optics to modify the polarization of light at any location.
  • the DIC inspection system 100 may include a polarizer 130 to provide a linearly- polarized illumination beam 104 on the shearing prism 106.
  • the DIC inspection system 100 may include an analyzer 132 to isolate the reflected light 124 associated with reflections of the sheared beams 108 and facilitate high-contrast interference at the detector 116.
  • the DIC inspection system 100 may include a half-wave plate 134 to adjust the orientation of the linearly-polarized illumination beam 104 such that the sheared beams 108 have equal intensities.
  • the sheared beams 108 may have equal intensities when the polarization of the illumination beam 104 is oriented at 45 degrees with respect to the optic axes of one or more birefringent materials forming the shearing prism 106. Accordingly, a half-wave plate 134 may allow precise adjustment of the polarization of the illumination beam 104 on the shearing prism 106 regardless of the orientation or initial polarization of the illumination source 102.
  • the DIG inspection system 100 may include beam-conditioning optics to control, shape, or otherwise adjust the properties of light at any point in the DIC inspection system 100.
  • the beam-conditioning optics may include, but are not limited to, one or more spectral filters, one or more neutral density filters, one or more apertures, or one or more homogenizers.
  • the illumination source 102 may include any type of light source known in the art suitable for generating an illumination beam 104 including, but not limited to, a laser source, a light-emitting diode (LED) source, a lamp source, or a laser-sustained plasma (LSP) source. Further, the illumination source 102 may generate an illumination beam 104 having any selected spectrum. For example, the illumination beam 104 may include any combination of ultraviolet (UV), visible, or infrared (IR) light. By way of another example, the illumination beam 104 may include short-wavelength light such as, but not limited to, extreme ultraviolet (EUV), deep ultraviolet (DUV), or vacuum ultraviolet (VUV) light.
  • EUV extreme ultraviolet
  • DUV deep ultraviolet
  • VUV vacuum ultraviolet
  • the illumination source 102 is a tunable light source, where the spectrum (e.g., the center wavelength, the bandwidth, or the like) of the illumination beam 104 may be selectively tuned.
  • the DIC inspection system 100 may operate as a multi-wavelength inspection system.
  • the illumination source 102 may include any type of tunable light source known in the art.
  • the illumination source 102 includes a light emitter with a tunable emission spectrum such as, but not limited to, a tunable laser source.
  • the illumination source 102 inciudes a broadband light source coupled to one or more spectra! filters to provide the illumination beam 104 with a selected spectrum.
  • the spectral filters may include one or more selectively rotatable angulariy- tunable filters, where spectral filtering properties may be tuned by adjusting an incidence angle of light.
  • filters may include one or more fixed-spectrum filters that may be selectively placed in the optical path of broadband light from the broadband light source (e.g., using a filter wheel, one or more independent actuators, or the like) to provide the illumination beam 104 with a selected spectrum.
  • the detector 1 16 is a multi-pixel detector such that the DIC inspection system 100 may operate as a multi-pixel imaging system.
  • the sheared beams 108 may illuminate an extended portion of the sample 114, which is then imaged on to the detector 1 16 (e.g., using the objective lens 1 12 as well as any additional lenses suitable for imaging the sample 1 14).
  • a multi-pixel DIC inspection system 100 may provide relatively higher resolution and/or detection sensitivity than a single-pixel inspection system (e.g., a scanning DIC system).
  • the DIC inspection system 100 may combine a high-resolution objective lens 112, a low-noise detector 1 16, and a low-noise illumination source 102 to achieve highly sensitive defect detection and classification with resolution on the order of nanometers or lower in the longitudinal (e.g., height) direction and a few microns or lower in lateral directions.
  • the detector 1 16 may generate an image of a static or moving sample 1 14.
  • a detector 1 16 suitable for capturing an image of a static sample may include, but is not limited to, a charge-coupled device (CCD) or a complementary metal- oxide-semiconductor (CMOS) device.
  • CMOS complementary metal- oxide-semiconductor
  • a detector 116 suitable for capturing an image of a moving sample may include, but is not limited to, a line-scan sensor or a time delay integration (TDI) sensor.
  • TDI time delay integration
  • the DIC inspection system 100 inciudes a controller 136.
  • the controller 136 inciudes one or more processors 138 configured to execute a set of program instructions maintained in a memory medium 140, or memory.
  • the controller 136 may include one or more modules containing one or more program instructions stored in the memory medium 140 executable by the processors 138.
  • the processors 138 of a controller 136 may include any processing element known in the art. In this sense, the processors 138 may include any microprocessor-type device configured to execute algorithms and/or instructions.
  • the processors 138 may consist of a desktop computer, mainframe computer system, workstation, image computer, parallel processor, or any other computer system (e.g., networked computer) configured to execute a program configured to operate the DiC inspection system 100, as described throughout the present disclosure. It is further recognized that the term“processor” may be broadly defined to encompass any device having one or more processing elements, which execute program instructions from a non-transitory memory medium 140.
  • the memory medium 140 may include any storage medium known in the art suitable for storing program instructions executable by the associated processors 138.
  • the memory medium 140 may include a non-transitory memory medium.
  • the memory medium 140 may include, but is not limited to, a read-only memory, a random-access memory, a magnetic or optical memory device (e.g., disk), a magnetic tape, a solid state drive and the like. It is further noted that memory medium 140 may be housed in a common controller housing with the processors 138. In one embodiment, the memory medium 140 may be located remotely with respect to the physical location of the processors 138 and controller 136.
  • controller 136 may access a remote memory (e.g., server), accessible through a network (e.g., internet, intranet and the like). Therefore, the above description should not be interpreted as a limitation on the present invention but merely an illustration.
  • a remote memory e.g., server
  • a network e.g., internet, intranet and the like.
  • the controller 136 may be communicatively coupled with any components of the DIC inspection system 100.
  • the controller 136 receives data from one or more components of the DIG inspection system 100.
  • the controller 136 may receive images, or portions thereof, from the detector 1 16.
  • the controller 136 performs one or more processing steps of the present disclosure.
  • the controller 136 may receive images of the sample 114 generated with different induced phases (e.g., based on different configurations of the phase-adjustment sub-system 128) and perform one or more analysis steps (e.g., a phase retrieval analysis) to isolate the defect-induced phase shift.
  • the controller 136 may receive images of the sample 1 14, or a portion thereof, generated using different wavelengths of the illumination beam 104 and classify one or more details based on defect-induced phase shift for each wavelength.
  • the controller 136 may generate one or more control signals to direct or otherwise control components of the DIC inspection system 100.
  • the controller 136 may generate control signals for any component of the DIC inspection system 100 including, but not limited to, the detector 1 16, the translation stage 122, , or the illumination source 102.
  • FIGS. 2 through 9 defect detection and classification based on multi-wavelength DIC interferometry is described in greater detail in accordance with one or more embodiments of the present disclosure.
  • Contrast in an image generated by a DIC inspection system 100 may generally be related to interference between the reflected light 124 associated with the reflection of the sheared beams 108 from spatially offset portions of the sample.
  • the intensity of light in this case may be generally characterized as:
  • ⁇ c and 1 2 are intensities of the two sheared beams 108
  • R d is a reflectivity of a defect
  • R s is a reflectivity of the sample 1 14 surrounding a defect
  • Af ⁇ is a defect-induced phase difference
  • D ⁇ 3 ⁇ 4 is a system-induced phase difference.
  • the value of A ⁇ p s may be related to a particular location and/or orientation of the shearing prism 106.
  • the defect-induced phase difference (Af a ) may be based on both the defect height (h d ) with respect to the surrounding material and the difference between the RPC of the defect and the surrounding material.
  • the defect- induced phase difference ( Af ⁇ ) may be variously written as: where n is the refractive index, Df,. is a phase difference associated with a difference in RPC of the defect and surrounding portions of the sample 1 14 and h T0T is an apparent height of the defect (e.g., apparent OPD of the defect) based on both the actual height h d and an additional contribution h RPC based on the RPC difference between the defect and the sample 114 surrounding the defect.
  • the factor of 2 in equation (3) accounts for the round-trip path of reflected light in the DIC inspection system 100.
  • RPC generally depends on various factors such as, but not limited to, material composition, material size, and wavelength of incident light. Accordingly, comparing the defect-induced phase (Af a ) and/or the RPC difference (Af t ) itself associated with multiple wavelengths may facilitate classification of a defect based on these factors.
  • FIGS. 2 and 3 show the RPC of metals and non-metals as a function of defect thickness (size) at a common wavelength.
  • FIG. 2 is a simulated plot 202 of the RPC of two metals, Tungsten (W) and Copper (Cu) on a silicon substrate as a function of thickness at a wavelength of 365 nm, in accordance with one or more embodiments of the present disclosure.
  • FIG. 3 is a simulated plot 302 of the RPC of Si0 2 on a silicon substrate as a function of thickness at a wavelength of thickness at a wavelength of 365 nm, in accordance with one or more embodiments of the present disclosure.
  • FIGS. 2 and 3 include simulations of thin films using a thin film model, which provides a first approximation of the RPC of associated defects.
  • the RPC for metals is constant when the defect size is greater than approximately 100 nm. Further, the amount of RPC varies substantially based on the composition of the metal. In contrast, as illustrated in FIG. 3, the RPC of Si0 2 is strongly dependent on thickness. Further, it is noted that FIG. 3 illustrates a wrapped phase with a modulus of 360 degrees (2p rad).
  • FIGS. 4 and 5 show the RPC of metals and non-metals as a function of defect thickness (size) at multiple wavelengths (365 nm and 405 nm), in accordance with one or more embodiments of the present disclosure. Accordingly, FIGS. 4 and 5 illustrate how variations of the RPC as a function of wavelength may be exploited for defect classification.
  • FIG. 4 is a plot 402 of copper (Cu) on a silicon substrate as a function of thickness, in accordance with one or more embodiments of the present disclosure.
  • FIG. 5 is a plot 502 of copper S1O2 on a silicon substrate as a function of thickness, in accordance with one or more embodiments of the present disclosure.
  • the RPC of metals exhibits a relatively small dependence on wavelength (e.g., less than 5 degrees) for nearly all sizes greater than 200 nm.
  • the RPC of Si02 exhibits a relatively large dependence on wavelength (e.g., greater than 90 degrees) for sizes greater than approximately 200 nm.
  • the RPC of metals varies based on the particular composition of the metal, but is relatively constant as a function of illumination wavelength and size regardless of the composition.
  • the RPC of non-metals as exemplified by, but not limited to, SiOa, exhibits a relatively large dependence on for defect sizes greater than approximately 200 nm.
  • a defect may be classified as a metal or a non-metal based on a measured variation of the RPC as a function of wavelength, where variations beyond a selected threshold indicate a non-metallic defect.
  • the intensity 1 of light at a particular position on the detector 116 depends in part on the optical phase (f ) at the detector 116 associated with the reflected light 124 recombined by the shearing prism 106. Further, this optical phase (f) may include a system-induced phase shift (D 5 ) as well as a defect- induced phase-shift (Af ⁇ ).
  • the defect-induced phase-shift ( Df ⁇ ) is extracted or otherwise separated from the system-induced phase shift (Df 5. ) using a phase retrieval analysis (e.g., by the controller 136) to isolate the impact of the RPC on the intensity /.
  • the defect-induced phase-shift ⁇ Df ⁇ ) may be extracted or otherwise separated from the system-induced phase shift (Df 5 ) using any technique or combination of techniques known in the art.
  • the defect-induced phase-shift (Df ⁇ ) may be extracted using a phase-shifting analysis.
  • the defect-induced phase-shift (Af a ) associated with an identified defect may be determined based on multiple images of the defect with different (e.g., selected) system-induced phase shifts (D 5 ) at each wavelength.
  • the system-induced phase shift (D , ) may be adjusted using a phase-adjustment sub-system 128, which may include, but is not limited to, an actuator to translate the shearing prism 106 along the shearing direction 110.
  • the variations in the intensity (I) in response to the sequence of selected system-induced phase shifts (Af $ ) may isolate the contribution of the selected system-induced phase shifts (Af $ ) such that the defect-induced phase-shift (Af a ) may be determined.
  • the phase retrieval analysis may be applied for multiple images at each of two or more wavelengths in order to extract the defect-induced phase-shift ( Af a ) associated with each of the two or more wavelengths.
  • the defect-induced phase-shift ( Af ⁇ ) may be separated from the system- induced phase shifts ( Df 5 ) using a low-pass filter such as, but not limited to, a moveable median filter.
  • system-induced phase shifts (Df 3 ) may result from sources such as, but not limited to, a non-uniform difference between the sheared beams 108 (e.g., extraordinary and ordinary beams from the shearing prism 106) or a local slope associated with natural or sample-holder-induced variations of the surface of the sample 1 14. Further, these system-induced phase shifts ( Af 5 ) may have a relatively slowly-varying frequency such that the low-pass filter may separate a defect- induced phase-shift ( Af ⁇ ) from the system-induced phase shifts (D 5 ).
  • the multiple images with different selected system-induced phase shifts (Af $ ) may be generated using any imaging technique known in the art.
  • the multiple images may be taken sequentially using different selected system- induced phase shifts (Af $ ) while the sample 1 14 remains stationary.
  • the multiple images may be taken using multiple sequential scans using different selected system-induced phase shifts ⁇ Af e ).
  • FIG. 6 includes simulated plots 602-608 of the intensity (/) of a defect generated using multiple sequential scans with four different selected system-induced phase shifts ( Af 3 ) (0 degrees, 90 degrees, 180 degrees, and 270 degrees, respectively), in accordance with one or more embodiments of the present disclosure.
  • FIG. 7 includes a plot 702 of a defect profile (e.g., a height ( h d )) and a plot 704 of simulated and reconstructed defect-induced phase-shifts ( Af a ) based on the plots in FIG. 6, in accordance with one or more embodiments of the present disclosure. As illustrated in F!G.
  • a phase retrieval analysis based on multiple images based on different selected system-induced phase shifts may accurately extract the defect-induced phase-shift (Df a ). Accordingly, the DIC inspection system 100 may classify a defect based on a comparison of defect-induced phase-shifts ( Df a ) associated with two or more wavelengths.
  • FIGS. 8 and 9 phase extraction of a defect-free sample 1 14 based on multiple static images of a stationary sample with eleven selected system- induced phase shifts (Df 3 ) are shown.
  • FIG. 8 includes three of the eleven measured images 802-806 of a defect-free sample 114, in accordance with one or more embodiments of the present disclosure.
  • FIG. 9 is a plot 902 of a reconstructed phase- shift of the sample 1 14 imaged in FIG. 8, in accordance with one or more embodiments of the present disclosure in particular, the shearing direction 110 associated with FIGS. 8 and 9 is 45 degrees in the respective plots. Further, FIGS. 8 and 9 may demonstrate the ability to extract (e.g.
  • phase extraction techniques disclosed herein may be utilized to characterize phase shifts induced by inherent variations of the surface of the sample 114 as well as phase shifts induced by one or more defects.
  • a difference between the RPC and a surrounding portion of the sample 114 may manifest as a variation in the defect-induced phase-shift ( Df a ) such that a comparison of the defect-induced phase-shift ( Df ⁇ ) for different wavelengths may facilitate classification of the defects.
  • Table 2 below provides simulated data associated with defect-induced phase-shifts ( Df a ) associated with multiple wavelengths is shown for defect sizes in the range of 200-350 nm, in accordance with one or more embodiments of the present disclosure.
  • Tables 2 includes the simulated values of h RP and k T0T .
  • defects are classified based on a ratio of the defect-induced phase-shifts (Df a ) associated with two wavelengths, which is equivalent to the ratio of h T o T shown in Table 2 based on equation (3) above.
  • defects may be classified as non-metal metal if the absolute value of the ratio of the defect-induced phase-shifts (Df ⁇ ) is lower than a selected threshold.
  • the threshold may be any selected value and may be adjusted based on the specific materials of interest and/or wavelengths used. For example, a threshold of 0.9 would enable classification of the Cu defect as a metal and the Si02 defect as a non-metal.
  • FIG. 10 is a flow diagram illustrating steps performed in a method 1000 for classifying defects, in accordance with one or more embodiments of the present disclosure. Applicant notes that the embodiments and enabling technologies described previously herein in the context of the DIG inspection system 100 should be interpreted to extend to method 1000. It is further noted, however, that the method 1000 is not limited to the architecture of the DIG inspection system 100.
  • the method 1000 includes a step 1002 of receiving a first set of images of a defect on a sample with a first selected illumination spectrum and two or more selected induced phase differences between two sheared illumination beams from a differential interference contrast imaging tool.
  • the method 1000 includes a step 1004 of determining a first defect-induced phase shift based on the first selected illumination spectrum.
  • the method 1000 includes a step 1006 ofreceiving a second set of images of a defect on the sample with a second selected illumination spectrum different than the first illumination spectrum and two or more selected induced phase differences between the two sheared illumination beams from the differential interference contrast imaging tool.
  • the method 1000 includes a step 1008 of determining a second defect-induced phase shift based on the second selected illumination spectrum.
  • the steps 1004 and 1008 may include applying a phase retrieval algorithm incorporating a phase-shifting technique using the first set of images.
  • the method 1000 includes a step 1010 of classifying the defect as a metal or a non-metal based on a comparison of the first defect-induced phase shift to the second defect-induced phase shift.
  • the step 1010 may include, but is not limited to, classifying the defect as a metal or a non- metal based on a ratio of the first defect-induced phase shift with respect to the second defect-induced phase shift.
  • the step 1010 includes classifying the defect as a non-metal if the absolute value of the ratio of the first defect-induced phase shift with respect to the second defect-induced phase shift is lower than a selected threshold.
  • any two components so associated can also be viewed as being “connected” or “coupled” to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “couplable” to each other to achieve the desired functionality.
  • Specific examples of couplabie include but are not limited to physically interactable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interactable and/or logically interacting components.

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Abstract

Un système d'inspection peut comprendre un contrôleur couplé à un outil d'imagerie à contraste interférentiel différentiel pour générer des images d'un échantillon sur la base d'un éclairage avec deux faisceaux d'éclairage dédoublés. Le contrôleur peut déterminer un premier déphasage induit par un défaut sur la base d'un premier ensemble d'images d'un défaut sur l'échantillon avec un premier spectre d'éclairage sélectionné et au moins deux déphasages induits sélectionnés entre les deux faisceaux d'éclairage dédoublés, déterminer un second déphasage induit par un défaut sur la base d'un second ensemble d'images du défaut avec un second spectre d'éclairage sélectionné et au moins deux déphasages induits sélectionnés entre les deux faisceaux d'éclairage dédoublés, et classifier le défaut comme métallique ou non métallique sur la base d'une comparaison du premier déphasage avec le second déphasage.
PCT/US2019/048680 2018-09-04 2019-08-29 Interférométrie à longueurs d'onde multiples pour la classification de défauts WO2020051046A1 (fr)

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